Because of the extreme suffering and high economic costs associated with HIV infection, it is imperative that humane, clinically sound, and cost-effective management strategies be identified for HIV-infected patients. Furthermore, policy decisions regarding research priorities must be made in the context of a rapidly expanding body of knowledge concerning the diagnosis, treatment, and natural history of HIV-related illnesses. We propose the development of decision-analytic models to aid in both the determination of optimal clinical management strategies and in the assessment of the potential impact that policy initiatives would have on the cost and outcomes of patient care. We will first develop a model for persons presenting with central nervous system disorders (CNS model). We will then integrate the CNS model with our previously developed model for respiratory disorders. These two organ systems represent the most frequent sites of fatal complications in AIDS patients. We intend to use the integrated model to explore the feasibility of developing a comprehensive natural clinical history model of HIV infection. Many HIV-related central nervous system diseases are potentially treatable, but rapidly fatal if undiagnosed. Furthermore, there is considerable disagreement over what constitutes appropriate clinical management of HIV-infected patients, and diagnostic strategies vary widely with respect to cost and accuracy. Our CNS model will assess the life-expectancy, quality-adjusted life expectancy, short term morbidity, cost, and cost-effectiveness of all clinically reasonable management strategies in patients presenting with either focal neurologic deficits, or with headache and/or confusion in the absence of focal neurologic deficits. We will use this model to identify cost-effective management strategies for each symptom presentation and for particular subgroups of patients as defined by presence or absence of a previous AIDS-defining diagnoses. Analyses with this model will allow us to assess the impact that improvements in the treatment of CNS disorders, or changes in practice, such as screening for Toxoplasma gondii, would have on the health and economic outcomes of care for patients presenting with neurologic symptoms in each subgroup. The completed CNS model will be integrated with our previously developed respiratory model, thus permitting the evaluation of the impact of research advances on cost-effectiveness of care in a much broader context. More specifically, we will assess the relative impact on outcomes of care that research advances in respiratory complications have relative to research advances in CNS complications. In the process of developing the integrated model, we will have an opportunity to identify the natural history data necessary to construct a more comprehensive model, and to address the relevant computing issues.